The evolution of breast cancer (BC) treatments has resulted in tailored therapies for the different types and stages of BC. Each treatment has a profile of benefits and adverse effects which are taken into consideration when planning a treatment pathway. This study examines whether patients’ preferences are in line with what is considered important from decision makers viewpoint.

An online discrete choice experiment was conducted in six European countries (France, Germany, Ireland, Poland, Spain, UK) with BC patients. Six attributes were included: overall survival (OS), hyperglycemia, rash, pain, functional well-being (FWB), and out-of-pocket payment (OOP). Sixteen choice sets with two hypothetical treatments and a “No treatment” option were presented. Data were analyzed with the use of heteroscedastic conditional, mixed logistic, and latent class models. Marginal rate of substitution (MRS) were estimated for OOP versus the rest of attributes to establish the ranking of preferences for each attribute.

Two hundred and forty-seven patients with advanced or metastatic BC and 314 with early-stage BC responded. Forty-nine percent of patients were < 44 years old and 65 percent had completed university education. The MRS of the analysis demonstrated that “severe pain” is the highest dis-preferred attribute level, followed by “severe impairment in FWB” and OS. Four classes of patients as “decision makers” were identified.

This study suggests that there is heterogeneity in treatment preferences of BC patients depending on their sociodemographic and disease-related characteristics. In combination with clinical guidelines, patient preferences can support the selection and tailoring of treatment options.

A few studies examine the time evolution of delirium in long-term care (LTC) settings. In this work, we analyze the multivariate Delirium Index (DI) time evolution in LTC settings.

The multivariate DI was measured weekly for six months in seven LTC facilities, located in Montreal and Quebec City. Data were analyzed using a hidden Markov chain/latent class model (HMC/LC).

The analysis sample included 276 LTC residents. Four ordered latent classes were identified: fairly healthy (low “disorientation” and “memory impairment,” negligible other DI symptoms), moderately ill (low “inattention” and “disorientation,” medium “memory impairment”), clearly sick (low “disorganized thinking” and “altered level of consciousness,” medium “inattention,” “disorientation,” “memory impairment” and “hypoactivity”), and very sick (low “hypoactivity,” medium “altered level of consciousness,” high “inattention,” “disorganized thinking,” “disorientation” and “memory impairment”). Four course types were also identified: stable, improvement, worsening, and non-monotone. Class order was associated with increasing cognitive impairment, frequency of both prevalent/incident delirium and dementia, mortality rate, and decreasing performance in ADL.

Four ordered latent classes and four course types were found in LTC residents. These results are similar to those reported previously in acute care (AC); however, the proportion of very sick residents at enrolment was larger in LTC residents than in AC patients. In clinical settings, these findings could help identify participants with a chronic clinical disorder. Our HMC/LC approach may help understand coexistent disorders, e.g. delirium and dementia.

The phenotypic variance observed in panic disorder (PD) appears to be best captured by a respiratory and non-respiratory panic subtype. We compared respiratory and non-respiratory panic subtypes across a series of external validators (temporal stability, psychiatric co-morbidity, treatment response) to determine whether subtypes are best conceptualized as differing: (1) only on their symptom profiles with no other differences between them; (2) on a quantitative (i.e. severity) dimension only; or (3) qualitatively from one another.

Data from a large epidemiological survey (National Epidemiologic Survey on Alcohol and Related Conditions) and a clinical trial (Cross-National Collaborative Panic Study) were used. All analytic comparisons were examined within a latent class framework.

High temporal stability of panic subtypes was observed, particularly among females. Respiratory panic was associated with greater odds of lifetime major depression and a range of anxiety disorders as well as increased treatment utilization, but no demographic differences. Treatment outcome data did not suggest that the two PD subtypes were associated with differential response to either imipramine or alprazolam.

These data suggest that respiratory and non-respiratory panic represent valid subtypes along the PD continuum, with the respiratory variant representing a more severe form of the disorder.

Panic disorder (PD) is a heterogeneous syndrome that can present with a variety of symptom profiles that potentially reflect distinct etiologic pathways. The present study represents the most comprehensive examination of phenotypic variance in PD with and without agoraphobia for the purpose of identifying clinically relevant and etiologically meaningful subtypes.

Latent class (LC) and factor mixture analysis were used to examine panic symptom data ascertained from three national epidemiologic surveys [Epidemiological Catchment Area (ECA), National Comorbidity Study (NCS), National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 1], a twin study [Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)] and a clinical trial (Cross-National Collaborative Panic Study [CNCPS]).

Factor mixture models (versus LC) generally provided better fit to panic symptom data and suggested two panic classes for the ECA, VATSPSUD and CNCPS, with one class typified by prominent respiratory symptoms. The NCS yielded two classes, but suggested both qualitative and quantitative differences. The more contemporary NESARC sample supported a two and three class model, with the three class model suggesting two variants of respiratory panic. The NESARC's three class model continued to provide the best fit when the model was restricted to a more severe form of PD/panic disorder with agoraphobia.

Results from epidemiologic and clinical samples suggest two panic subtypes, with one subtype characterized by a respiratory component and a second class typified by general somatic symptoms. Results are discussed in light of their relevance to the etiopathogenesis of PD.

Obsessive–compulsive disorder (OCD) is probably an etiologically heterogeneous condition. Many patients manifest other psychiatric syndromes. This study investigated the relationship between OCD and co-morbid conditions to identify subtypes.

Seven hundred and six individuals with OCD were assessed in the OCD Collaborative Genetics Study (OCGS). Multi-level latent class analysis was conducted based on the presence of eight co-morbid psychiatric conditions [generalized anxiety disorder (GAD), major depression, panic disorder (PD), separation anxiety disorder (SAD), tics, mania, somatization disorders (Som) and grooming disorders (GrD)]. The relationship of the derived classes to specific clinical characteristics was investigated.

Two and three classes of OCD syndromes emerge from the analyses. The two-class solution describes lesser and greater co-morbidity classes and the more descriptive three-class solution is characterized by: (1) an OCD simplex class, in which major depressive disorder (MDD) is the most frequent additional disorder; (2) an OCD co-morbid tic-related class, in which tics are prominent and affective syndromes are considerably rarer; and (3) an OCD co-morbid affective-related class in which PD and affective syndromes are highly represented. The OCD co-morbid tic-related class is predominantly male and characterized by high conscientiousness. The OCD co-morbid affective-related class is predominantly female, has a young age at onset, obsessive–compulsive personality disorder (OCPD) features, high scores on the ‘taboo’ factor of OCD symptoms, and low conscientiousness.

OCD can be classified into three classes based on co-morbidity. Membership within a class is differentially associated with other clinical characteristics. These classes, if replicated, should have important implications for research and clinical endeavors.